1. Field of the Invention
The invention relates to methods for storing and updating descriptions of customer behavior in databases of information relating to customer transactions.
2. Art Background
A company that conducts many business transactions with individual customers will often find it advantageous to maintain customer profiles that describe the current transactional behavior of some or all individual customers. Such profiles are advantageously updated each time a customer conducts a transaction.
By way of example, a telephone service provider might profile its customers on the basis of variables such as day-of-week, time-of-day and duration of calls, call origin and destination, and the like. A customer profile is useful, e.g., for fraud detection. That is, if a call made by a purported customer diverges markedly from that customer's profile, it is reasonable to suspect that the caller is fraudulently impersonating the purported customer.
Of course, such profiles are useful in regard not only to customers in the strict sense of the term, but more generally, they are useful in regard to parties to transactions of any kind that has distinguishing features that can be used to discriminate among individual parties. We will continue to apply, herein, the term customer to any such party, but it should be borne in mind that the term is meant in the broad, and not in the restrictive, sense.
Several challenges confront the practitioner who wishes to compile a database of customer profiles. One challenge is to select an appropriate amount of information for storage. Enough information should be stored to provide a useful characterization of the profiled customers. On the other hand, the total amount of stored information should not overwhelm the storage and processing capacities of the database system. Advantageously, the amount of data allocated for each customer, i.e., the profile length, is fixed, because computers can generally process fixed-length profiles faster and more efficiently than they can process variable-length profiles. A limitation to fixed-length profiles, however, makes it even more difficult to select an appropriate amount of information for storage.
A typical profile is a collection of histograms, also referred to herein as “profile components,” in each of which a relative frequency of transactions is plotted for each of a plurality of intervals, or bins, along an axis. Measured along the axis is a variable such as time or cost. A time axis might represent, e.g., time of occurrence of a telephone call, call duration, or interval between calls. The variable measured along the axis may be continuous, such as time, or it may be discrete, such as geographical zone (which takes on discrete values such as international and domestic).
A further challenge confronting the practitioner is to choose the appropriate level of resolution along the measurement axis; that is, the appropriate widths of the bins. In general, this is a problem whenever the variable has continuous values or values that fall on many levels. Such variables include the time-based measurements listed above. In regard, for example, to relative frequencies of call occurrence, a pair of gross counts of weekday calls and weekend calls, respectively, might have a relatively large amount of power for discriminating between customers. If that were so, there would be relatively little need to count calls on a daily, much less an hourly, basis. In such a case, choosing coarse rather than fine temporal resolution would be advantageous because such a choice would leave storage space available for a further variable having potentially high discriminating power.